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hackathon-submission-prep黑客马拉松提交准备

Agent Skill

hackathon-submission-prep 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

346

周安装

14

GitHub Stars

1

下载量

109
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:hackathon-submission-prep(黑客马拉松提交准备)
来源仓库:https://github.com/bernieweb3/hackathon-ai-devkit
仓库路径:skills/hackathon-submission-prep
安装命令:
npx skills add https://github.com/bernieweb3/hackathon-ai-devkit --skill hackathon-submission-prep
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/bernieweb3/hackathon-ai-devkit --skill hackathon-submission-prep

简介

用于处理 GitHub 仓库、Issue 和 Pull Request 信息,协助代码协作与变更管理。

  • 适合在需要围绕仓库状态或代码变更进行整理时使用,支持多宿主环境。
  • 通过 npx skills add 命令从指定仓库安装,具体用法请参考原始 README。
  • 安装前应确认权限范围、维护状态,并评估是否会触发联网或文件操作。
  • 注意:避免直接执行未经验证的命令,防止误改生产环境代码。

SKILL.md

hackathon-submission-prep

Goal

Compile and validate all required hackathon submission artifacts into a complete, polished submission package ready for upload.


Trigger Conditions

Use this skill when:

  • The demo video is uploaded and the pitch deck is finalized
  • Submission deadline is approaching and artifacts must be validated
  • A submission platform (Devpost, Dorahacks, etc.) requires a structured description
  • The team needs a checklist of what is complete versus what is still missing
  • Invoked during Phase 8; submit output to the platform at least 1 hour before the deadline

Inputs

InputTypeRequiredDescription
project_titlestringYesName of the project
taglinestringYesOne-sentence description
problem_statementstringYesThe problem being solved
solution_summarystringYesHow the project solves it
tech_stackstring[]YesTechnologies used
team_membersobject[]YesTeam member names and roles
demo_urlstringNoLive demo URL
video_urlstringNoDemo video URL
repo_urlstringYesSource code repository URL
trackstringYesHackathon track being entered
submission_platformstringNoPlatform name (e.g., Devpost, Dorahacks)
custom_fieldsobject[]NoPlatform-specific required fields

Outputs

OutputDescription
submission_descriptionFull formatted project description for submission
short_description280-character tagline/elevator pitch
artifact_checklistAll required submission items with completion status
missing_artifactsItems not yet provided that must be completed
submission_quality_score1–10 rating of submission readiness
last_mile_actionsFinal actions required before submitting

Rules

  1. submission_description must include: problem, solution, tech stack, team, and demo link.
  2. short_description must be 280 characters or fewer.
  3. artifact_checklist must verify: repo URL accessible, README exists, demo video linked, team listed.
  4. Assign submission_quality_score using: completeness (40%), clarity (30%), impact framing (30%).
  5. last_mile_actions must be ordered by priority with estimated time per action.
  6. Flag any missing required field from custom_fields as a blocking missing_artifact.
  7. Do not submit placeholder text; flag any [TBD] fields as incomplete in missing_artifacts.

Output Format

submission_description: |
  <Full Markdown submission text>

short_description: "<≤280 characters>"

artifact_checklist:
  - item: "<artifact name>"
    status: "<complete|incomplete|missing>"
    url_or_value: "<link or value if complete>"

missing_artifacts:
  - item: "<name>"
    blocking: <true|false>
    action_required: "<what to do>"

submission_quality_score:
  score: <1-10>
  breakdown:
    completeness: <1-10>
    clarity: <1-10>
    impact_framing: <1-10>

last_mile_actions:
  - priority: <number>
    action: "<what to do>"
    estimated_minutes: <number>

Example

Input:

project_title: "AnchorAI"
tagline: "An AI companion that remembers your emotional journey so you never have to start over."
problem_statement: "College students wait 6 weeks for counseling while anxiety compounds daily."
solution_summary: "GPT-4 with Redis-backed session memory for always-available, context-aware emotional support."
tech_stack: ["Python", "FastAPI", "React", "Redis", "OpenAI GPT-4"]
team_members:
  - name: "Alex"
    role: "Backend"
  - name: "Sam"
    role: "Frontend"
  - name: "Jordan"
    role: "Design"
repo_url: "https://github.com/team/anchorai"
track: "AI for Mental Health"
submission_platform: "Devpost"

Output:

submission_description: |
  ## Inspiration
  40% of college students report anxiety as their top health concern, yet the average campus counseling wait is 6 weeks. Most students give up before they're seen.

  ## What It Does
  AnchorAI is a GPT-4 powered emotional support companion that remembers your history across sessions. It opens every conversation with context from your last check-in — so you never have to re-explain your situation.

  ## How We Built It
  Python FastAPI backend with OpenAI GPT-4 API. Session summaries stored in Redis and injected into the system prompt. React frontend with a clean single-page chat UI.

  ## Challenges
  Getting memory injection to stay within GPT-4 context window limits required hard-capping summaries at 150 tokens and testing multiple summarization prompts.

  ## Accomplishments
  Working live demo with genuine session memory recall. Crisis escalation card renders on distress detection.

  ## What We Learned
  The emotional framing of AI responses matters more than technical sophistication. Users notice tone before they notice features.

  ## What's Next
  Human counselor escalation. University licensing. Multi-session longitudinal mood tracking.

short_description: "AnchorAI: GPT-4 emotional support companion that remembers your mental health journey. No waitlist. No starting over. Always there. 🧠"

artifact_checklist:
  - item: "Source code repository"
    status: "complete"
    url_or_value: "https://github.com/team/anchorai"
  - item: "Demo video"
    status: "complete"
    url_or_value: "https://youtube.com/watch?v=demo"
  - item: "Live demo URL"
    status: "incomplete"
    url_or_value: ""
  - item: "README with setup instructions"
    status: "complete"
    url_or_value: "https://github.com/team/anchorai#readme"

missing_artifacts:
  - item: "Live demo URL"
    blocking: false
    action_required: "Deploy to Railway or Render; update Devpost submission with URL"

submission_quality_score:
  score: 8
  breakdown:
    completeness: 9
    clarity: 8
    impact_framing: 8

last_mile_actions:
  - priority: 1
    action: "Deploy live demo to Railway and update Devpost URL field"
    estimated_minutes: 20
  - priority: 2
    action: "Add 3 screenshots to Devpost gallery"
    estimated_minutes: 10
  - priority: 3
    action: "Confirm repo is public and README loads correctly"
    estimated_minutes: 5

Context Files

Knowledge Base

  • knowledge/hackathon-submission-guidelines.md
  • knowledge/hackathon-winning-patterns.md
  • knowledge/hackathon-pitch-strategy.md

Playbooks

  • playbooks/hackathon-workflow.md

适合场景

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02

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能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

38.59%
按下载量换算42

Claude

27.47%
按下载量换算30

Cursor

18.08%
按下载量换算20

Gemini CLI

10.2%
按下载量换算11

安全审计

Gen Agent Trust Hub

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Socket

通过

Snyk

可疑

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

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